Drops the original column from the dataframe once bins are made. Throws an error if the same column has multiple bin cols.
drop_original_cols(.data, ..., restore_names = FALSE)dataframe output from bin_cols
tidyselect. default chooses all cols created from binning
Logical, default FALSE. rename the binned cols with the original column names?
dataframe
iris %>%
bin_cols(Sepal.Length) %>%
bin_cols(Sepal.Width, pretty_labels = TRUE) -> iris1
iris1
#> # A tibble: 150 × 7
#> Sepal.Width_fr9 Sepal.Length_fr10 Sepal.Length Sepal.Width Petal.Length
#> <fct> <int> <dbl> <dbl> <dbl>
#> 1 (3.4,3.61] 3 5.1 3.5 1.4
#> 2 (2.8,3] 2 4.9 3 1.4
#> 3 (3.1,3.2] 1 4.7 3.2 1.3
#> 4 (3,3.1] 1 4.6 3.1 1.5
#> 5 (3.4,3.61] 2 5 3.6 1.4
#> 6 (3.61,4.4] 4 5.4 3.9 1.7
#> 7 (3.2,3.4] 1 4.6 3.4 1.4
#> 8 (3.2,3.4] 2 5 3.4 1.5
#> 9 (2.8,3] 1 4.4 2.9 1.4
#> 10 (3,3.1] 2 4.9 3.1 1.5
#> # … with 140 more rows, and 2 more variables: Petal.Width <dbl>, Species <fct>
iris1 %>%
drop_original_cols(restore_names = TRUE)
#> # A tibble: 150 × 5
#> Sepal.Width Sepal.Length Petal.Length Petal.Width Species
#> <fct> <int> <dbl> <dbl> <fct>
#> 1 (3.4,3.61] 3 1.4 0.2 setosa
#> 2 (2.8,3] 2 1.4 0.2 setosa
#> 3 (3.1,3.2] 1 1.3 0.2 setosa
#> 4 (3,3.1] 1 1.5 0.2 setosa
#> 5 (3.4,3.61] 2 1.4 0.2 setosa
#> 6 (3.61,4.4] 4 1.7 0.4 setosa
#> 7 (3.2,3.4] 1 1.4 0.3 setosa
#> 8 (3.2,3.4] 2 1.5 0.2 setosa
#> 9 (2.8,3] 1 1.4 0.2 setosa
#> 10 (3,3.1] 2 1.5 0.1 setosa
#> # … with 140 more rows
iris1 %>%
drop_original_cols(restore_names = FALSE)
#> # A tibble: 150 × 5
#> Sepal.Width_fr9 Sepal.Length_fr10 Petal.Length Petal.Width Species
#> <fct> <int> <dbl> <dbl> <fct>
#> 1 (3.4,3.61] 3 1.4 0.2 setosa
#> 2 (2.8,3] 2 1.4 0.2 setosa
#> 3 (3.1,3.2] 1 1.3 0.2 setosa
#> 4 (3,3.1] 1 1.5 0.2 setosa
#> 5 (3.4,3.61] 2 1.4 0.2 setosa
#> 6 (3.61,4.4] 4 1.7 0.4 setosa
#> 7 (3.2,3.4] 1 1.4 0.3 setosa
#> 8 (3.2,3.4] 2 1.5 0.2 setosa
#> 9 (2.8,3] 1 1.4 0.2 setosa
#> 10 (3,3.1] 2 1.5 0.1 setosa
#> # … with 140 more rows